Senior Analyst - Payments Analytics

• Lead or participate in moderately complex programs and initiatives for data quality, governance, and metadata activities
• Design and conduct moderately complex analysis to identify and remediate data quality, data integrity, process, and control gaps
• Analyze, assess, and test data controls and data systems to ensure quality and risk compliance standards are met and adhere to data governance standards and procedures
• Identify data quality metrics and execute data quality audits to benchmark the state of data quality
• Develop recommendations for optimal approaches to resolve data quality issues and implement plans for assessing the quality of new data sources leveraging domain expertise and data, business, or process analysis to inform and support solution design
• Lead project teams and mentor less experienced staff members
• Drive planning and coordination on moderately complex remediation efforts acting as central point of contact
• Consult with clients to assess the current state of data and metadata quality within area of assigned responsibility
• Participate in cross-functional groups to develop companywide data governance strategies
• Provide input into communication routines with stakeholders, business partners, and experienced leaders

• 4+ years of Data Management, Business Analysis, Analytics, or Project Management experience
• 4+ years of SQL experience
• 2+ years of experience with BI tools such as Tableau or Power BI
• Expert in SQL and Python
• Experience with Teradata/any other RDBMS
• Experience in creating DQs/Controls and with trend/variance analysis
• Knowledge and understanding of relational and no-SQL databases, structured, semi-structured, and unstructured data
• Knowledge and understanding of Big Data technologies (Data lake, cloud-based infrastructure), architectures that support real-time analytics
• Experience with master reference data such as Customer hierarchies, legal entities, and product taxonomies
• Have worked in Banking domain (preferably in Enterprise Payments or Treasury)

GCP, BigQuery, Azure Synapse Analytics, Python, Hadoop, Data Lakes, Big Data Accelerator technologies (Dremio, DataBricks, Snowflake) to optimize big data visualization